From 39b671c1e00a05ecea7dc3b88666c1913d3e08c0 Mon Sep 17 00:00:00 2001 From: Mr-Neutr0n <64578610+Mr-Neutr0n@users.noreply.github.com> Date: Fri, 6 Feb 2026 01:13:49 +0530 Subject: [PATCH] fix: NumPy >=1.24 compatibility - Replace deprecated np.float with np.float64 in my_awing_arch.py and torch2onnx.py (np.float was removed in NumPy 1.24) - Fix ValueError in align_img by explicitly casting t[0] and t[1] to float when building trans_params array Fixes #1019 Co-Authored-By: Claude Opus 4.5 --- src/face3d/models/arcface_torch/torch2onnx.py | 2 +- src/face3d/util/my_awing_arch.py | 2 +- src/face3d/util/preprocess.py | 2 +- 3 files changed, 3 insertions(+), 3 deletions(-) diff --git a/src/face3d/models/arcface_torch/torch2onnx.py b/src/face3d/models/arcface_torch/torch2onnx.py index fc26ab82..49884a92 100644 --- a/src/face3d/models/arcface_torch/torch2onnx.py +++ b/src/face3d/models/arcface_torch/torch2onnx.py @@ -6,7 +6,7 @@ def convert_onnx(net, path_module, output, opset=11, simplify=False): assert isinstance(net, torch.nn.Module) img = np.random.randint(0, 255, size=(112, 112, 3), dtype=np.int32) - img = img.astype(np.float) + img = img.astype(np.float64) img = (img / 255. - 0.5) / 0.5 # torch style norm img = img.transpose((2, 0, 1)) img = torch.from_numpy(img).unsqueeze(0).float() diff --git a/src/face3d/util/my_awing_arch.py b/src/face3d/util/my_awing_arch.py index cd565617..647fa111 100644 --- a/src/face3d/util/my_awing_arch.py +++ b/src/face3d/util/my_awing_arch.py @@ -15,7 +15,7 @@ def calculate_points(heatmaps): indexes = np.argmax(heatline, axis=2) preds = np.stack((indexes % W, indexes // W), axis=2) - preds = preds.astype(np.float, copy=False) + preds = preds.astype(np.float64, copy=False) inr = indexes.ravel() diff --git a/src/face3d/util/preprocess.py b/src/face3d/util/preprocess.py index b77a3a40..bb79ca8d 100644 --- a/src/face3d/util/preprocess.py +++ b/src/face3d/util/preprocess.py @@ -98,6 +98,6 @@ def align_img(img, lm, lm3D, mask=None, target_size=224., rescale_factor=102.): # processing the image img_new, lm_new, mask_new = resize_n_crop_img(img, lm, t, s, target_size=target_size, mask=mask) - trans_params = np.array([w0, h0, s, t[0], t[1]]) + trans_params = np.array([float(w0), float(h0), float(s), float(t[0]), float(t[1])]) return trans_params, img_new, lm_new, mask_new